code: def super_lm_moe_4b_diet():
      """Add mixture of experts with ~4B params and diet variables.
  
      Currently, hangs.  See this issue:
      https://github.com/tensorflow/tensorflow/issues/13351
  
      Returns:
        a hparams.
      """
      hparams = super_lm_moe()
      hparams.moe_num_experts = 128
      hparams.diet_experts = True
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import diet
  from tensor2tensor.utils import expert_utils
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 10 for calling a global function with example usage: super_lm_moe_4b_diet() and returns: hparams